Crear mapas de CampR con ggplot2.

La función ggplot2::map_data permite dar formato a Porc.map para pintarlo con ggplot2

Porc<-ggplot2::map_data(Porc.map) 
head(Porc)
hake<-CampR::maphist(1,50,"P16","Porc",out.dat=T,plot=F)
##    lan     lat     long  prof    peso.gr numero camp       peso
## 1    1 51.1471 -13.9298 531.5  12053.973    9.0 2016  12.053973
## 2    2 51.1011 -14.1830 628.5   3898.051    3.0 2016   3.898051
## 3    3 51.1372 -14.4533 638.5  12443.778    9.0 2016  12.443778
## 5    5 51.3002 -14.5562 593.5   4857.571    3.0 2016   4.857571
## 6    6 51.4554 -14.7745 639.0  11844.078    7.5 2016  11.844078
## 7    7 51.6273 -14.7835 572.0  44137.931   30.0 2016  44.137931
## 8    8 51.7889 -14.7824 485.5  12983.508   10.5 2016  12.983508
## 9    9 51.9642 -14.8531 495.5  13403.298   10.5 2016  13.403298
## 10  10 52.1994 -14.6672 406.0  50104.948   34.5 2016  50.104948
## 12  12 52.5173 -14.6387 412.0  49295.352   33.0 2016  49.295352
## 13  13 52.4468 -14.3837 347.0  40149.925   28.5 2016  40.149925
## 14  14 52.4544 -14.1025 311.5  31035.982   27.0 2016  31.035982
## 15  15 52.3609 -13.8595 349.0  28302.849   25.5 2016  28.302849
## 16  16 52.4373 -13.5133 361.5  44647.676   36.0 2016  44.647676
## 17  17 52.2815 -14.4153 352.0  35982.009   36.0 2016  35.982009
## 18  18 52.1550 -14.1128 344.0 108125.937   93.0 2016 108.125937
## 19  19 52.1276 -13.8451 403.0  80539.730   49.5 2016  80.539730
## 20  20 52.2124 -13.4927 436.5  97001.499   75.0 2016  97.001499
## 21  21 51.8779 -14.4495 360.0  39340.330   22.5 2016  39.340330
## 22  22 51.7396 -14.4448 384.0  67151.424   45.0 2016  67.151424
## 23  23 51.5521 -14.5670 507.0  53583.208   36.0 2016  53.583208
## 24  24 51.4685 -14.1850 446.0  61109.445   43.5 2016  61.109445
## 25  25 51.6924 -13.7936 502.5  16881.559   12.0 2016  16.881559
## 26  26 51.7289 -14.1079 381.0  44407.796   27.0 2016  44.407796
## 27  27 51.8743 -13.9758 379.5  36581.709   21.0 2016  36.581709
## 28  28 51.9700 -13.7536 442.0  34992.504   28.5 2016  34.992504
## 29  29 52.8863 -12.8234 428.0  83268.366   57.0 2016  83.268366
## 30  30 52.8840 -12.6118 417.0  43319.340   42.0 2016  43.319340
## 31  31 52.9644 -12.3519 326.0  92563.718  175.4 2016  92.563718
## 32  32 53.0122 -12.0771 233.0 112773.613  454.3 2016 112.773613
## 33  33 53.5221 -11.6332 215.0  20569.715   61.5 2016  20.569715
## 34  34 53.8113 -11.4031 252.0  48062.969   52.5 2016  48.062969
## 35  35 53.9852 -11.3952 287.0 174497.751  121.4 2016 174.497751
## 36  36 53.9398 -11.9261 370.5  75772.114   70.5 2016  75.772114
## 37  37 53.8415 -13.3700 362.0  30014.993   22.5 2016  30.014993
## 38  38 53.9635 -12.9041 596.0   4917.541    3.0 2016   4.917541
## 39  39 53.8543 -12.5745 380.5  20059.970   22.5 2016  20.059970
## 40  40 53.8930 -12.1672 375.5  78860.570   70.5 2016  78.860570
## 41  41 53.4660 -12.6767 297.5  54158.921   54.0 2016  54.158921
## 42  42 53.5125 -12.4703 315.0 118665.667   96.0 2016 118.665667
## 43  43 53.5162 -12.2190 329.5  37952.024   39.0 2016  37.952024
## 44  44 53.6031 -11.9335 296.0  74962.519   63.0 2016  74.962519
## 45  45 53.3864 -12.0448 280.5  46248.876  185.9 2016  46.248876
## 46  46 53.3008 -12.4400 360.5  94146.927  134.9 2016  94.146927
## 47  47 53.3623 -13.0208 271.5  27496.252   43.5 2016  27.496252
## 48  48 53.1860 -12.7345 353.5 117503.748  122.9 2016 117.503748
## 49  49 53.0288 -12.8775 379.0  83169.415  103.4 2016  83.169415
## 50  50 52.9543 -13.0919 361.5 204197.901  242.9 2016 204.197901
## 51  51 53.6493 -13.6562 270.0   5922.039    9.0 2016   5.922039
## 52  52 53.5385 -14.1104 330.0  25187.406   27.0 2016  25.187406
## 53  53 53.3838 -14.1155 225.5   7976.012   21.0 2016   7.976012
## 54  54 53.3056 -14.3913 350.5  68230.885   63.0 2016  68.230885
## 55  55 53.1272 -14.3615 232.5 111754.123   97.5 2016 111.754123
## 56  56 53.0369 -14.7581 663.5   2371.814    1.5 2016   2.371814
## 57  57 52.7801 -14.4977 401.5 157061.469  128.9 2016 157.061469
## 58  58 52.7032 -14.8204 643.5   6836.582    4.5 2016   6.836582
## 59  59 52.6840 -14.1928 324.5  38530.735   27.0 2016  38.530735
## 60  60 52.9205 -14.0399 205.5  11229.385   97.5 2016  11.229385
## 61  61 53.0984 -13.3226 237.5  13493.253   27.0 2016  13.493253
## 62  62 52.9616 -13.5822 209.5   6674.663   16.5 2016   6.674663
## 63  63 52.8107 -13.7734 212.0  10344.828   33.0 2016  10.344828
## 64  64 52.8229 -13.3382 288.0 105142.429  107.9 2016 105.142429
## 65  65 52.5408 -13.7273 313.0  18590.705   18.0 2016  18.590705
## 66  66 52.6534 -13.4919 308.5  82826.087   73.5 2016  82.826087
## 67  67 52.5408 -13.2676 419.5 167196.402  142.4 2016 167.196402
## 68  68 52.6955 -12.8570 502.5  53253.373   33.0 2016  53.253373
## 69  69 52.4507 -12.0559 330.0  40848.576   57.0 2016  40.848576
## 70  70 52.6219 -12.2969 401.0  90224.888   99.0 2016  90.224888
## 71  71 52.7735 -12.3392 371.0 168533.733  214.4 2016 168.533733
## 72  72 52.6403 -12.5908 523.0  94152.924   79.5 2016  94.152924
## 73  73 52.0337 -12.0698 721.5  16461.769    9.0 2016  16.461769
## 74  74 52.2069 -12.2312 697.5  87346.327   61.5 2016  87.346327
## 75  75 52.3952 -12.4823 601.5 180749.625  128.9 2016 180.749625
## 76  76 52.4483 -12.7148 603.5  49445.277   33.0 2016  49.445277
## 77  77 52.5373 -12.9262 550.0 114080.960   88.5 2016 114.080960
## 78  78 52.3982 -13.1029 543.5  66356.822   43.5 2016  66.356822
## 79  79 52.1400 -13.2446 606.5  34422.789   24.0 2016  34.422789
## 80  80 52.0511 -13.5145 495.5  40089.955   24.0 2016  40.089955
## 81  81 51.8873 -13.5214 581.0  42218.891   30.0 2016  42.218891
## 82  82 51.7320 -13.4943 710.5  17970.015   12.0 2016  17.970015
## 83  83 51.4595 -13.6170 723.5  23478.261   13.5 2016  23.478261
## 84  84 51.2955 -13.7462 686.0  13403.298    7.5 2016  13.403298
## 85  85 51.2869 -14.0051 522.5  51094.453   33.0 2016  51.094453
##    lan     lat     long  prof    peso.gr numero camp
## 1    1 51.1471 -13.9298 531.5  12053.973    9.0  P16
## 2    2 51.1011 -14.1830 628.5   3898.051    3.0  P16
## 3    3 51.1372 -14.4533 638.5  12443.778    9.0  P16
## 4    4 50.9836 -14.2370 748.0      0.000    0.0  P16
## 5    5 51.3002 -14.5562 593.5   4857.571    3.0  P16
## 6    6 51.4554 -14.7745 639.0  11844.078    7.5  P16
## 7    7 51.6273 -14.7835 572.0  44137.931   30.0  P16
## 8    8 51.7889 -14.7824 485.5  12983.508   10.5  P16
## 9    9 51.9642 -14.8531 495.5  13403.298   10.5  P16
## 10  10 52.1994 -14.6672 406.0  50104.948   34.5  P16
## 11  11 52.3914 -14.8265 611.0      0.000    0.0  P16
## 12  12 52.5173 -14.6387 412.0  49295.352   33.0  P16
## 13  13 52.4468 -14.3837 347.0  40149.925   28.5  P16
## 14  14 52.4544 -14.1025 311.5  31035.982   27.0  P16
## 15  15 52.3609 -13.8595 349.0  28302.849   25.5  P16
## 16  16 52.4373 -13.5133 361.5  44647.676   36.0  P16
## 17  17 52.2815 -14.4153 352.0  35982.009   36.0  P16
## 18  18 52.1550 -14.1128 344.0 108125.937   93.0  P16
## 19  19 52.1276 -13.8451 403.0  80539.730   49.5  P16
## 20  20 52.2124 -13.4927 436.5  97001.499   75.0  P16
## 21  21 51.8779 -14.4495 360.0  39340.330   22.5  P16
## 22  22 51.7396 -14.4448 384.0  67151.424   45.0  P16
## 23  23 51.5521 -14.5670 507.0  53583.208   36.0  P16
## 24  24 51.4685 -14.1850 446.0  61109.445   43.5  P16
## 25  25 51.6924 -13.7936 502.5  16881.559   12.0  P16
## 26  26 51.7289 -14.1079 381.0  44407.796   27.0  P16
## 27  27 51.8743 -13.9758 379.5  36581.709   21.0  P16
## 28  28 51.9700 -13.7536 442.0  34992.504   28.5  P16
## 29  29 52.8863 -12.8234 428.0  83268.366   57.0  P16
## 30  30 52.8840 -12.6118 417.0  43319.340   42.0  P16
## 31  31 52.9644 -12.3519 326.0  92563.718  175.4  P16
## 32  32 53.0122 -12.0771 233.0 112773.613  454.3  P16
## 33  33 53.5221 -11.6332 215.0  20569.715   61.5  P16
## 34  34 53.8113 -11.4031 252.0  48062.969   52.5  P16
## 35  35 53.9852 -11.3952 287.0 174497.751  121.4  P16
## 36  36 53.9398 -11.9261 370.5  75772.114   70.5  P16
## 37  37 53.8415 -13.3700 362.0  30014.993   22.5  P16
## 38  38 53.9635 -12.9041 596.0   4917.541    3.0  P16
## 39  39 53.8543 -12.5745 380.5  20059.970   22.5  P16
## 40  40 53.8930 -12.1672 375.5  78860.570   70.5  P16
## 41  41 53.4660 -12.6767 297.5  54158.921   54.0  P16
## 42  42 53.5125 -12.4703 315.0 118665.667   96.0  P16
## 43  43 53.5162 -12.2190 329.5  37952.024   39.0  P16
## 44  44 53.6031 -11.9335 296.0  74962.519   63.0  P16
## 45  45 53.3864 -12.0448 280.5  46248.876  185.9  P16
## 46  46 53.3008 -12.4400 360.5  94146.927  134.9  P16
## 47  47 53.3623 -13.0208 271.5  27496.252   43.5  P16
## 48  48 53.1860 -12.7345 353.5 117503.748  122.9  P16
## 49  49 53.0288 -12.8775 379.0  83169.415  103.4  P16
## 50  50 52.9543 -13.0919 361.5 204197.901  242.9  P16
## 51  51 53.6493 -13.6562 270.0   5922.039    9.0  P16
## 52  52 53.5385 -14.1104 330.0  25187.406   27.0  P16
## 53  53 53.3838 -14.1155 225.5   7976.012   21.0  P16
## 54  54 53.3056 -14.3913 350.5  68230.885   63.0  P16
## 55  55 53.1272 -14.3615 232.5 111754.123   97.5  P16
## 56  56 53.0369 -14.7581 663.5   2371.814    1.5  P16
## 57  57 52.7801 -14.4977 401.5 157061.469  128.9  P16
## 58  58 52.7032 -14.8204 643.5   6836.582    4.5  P16
## 59  59 52.6840 -14.1928 324.5  38530.735   27.0  P16
## 60  60 52.9205 -14.0399 205.5  11229.385   97.5  P16
## 61  61 53.0984 -13.3226 237.5  13493.253   27.0  P16
## 62  62 52.9616 -13.5822 209.5   6674.663   16.5  P16
## 63  63 52.8107 -13.7734 212.0  10344.828   33.0  P16
## 64  64 52.8229 -13.3382 288.0 105142.429  107.9  P16
## 65  65 52.5408 -13.7273 313.0  18590.705   18.0  P16
## 66  66 52.6534 -13.4919 308.5  82826.087   73.5  P16
## 67  67 52.5408 -13.2676 419.5 167196.402  142.4  P16
## 68  68 52.6955 -12.8570 502.5  53253.373   33.0  P16
## 69  69 52.4507 -12.0559 330.0  40848.576   57.0  P16
## 70  70 52.6219 -12.2969 401.0  90224.888   99.0  P16
## 71  71 52.7735 -12.3392 371.0 168533.733  214.4  P16
## 72  72 52.6403 -12.5908 523.0  94152.924   79.5  P16
## 73  73 52.0337 -12.0698 721.5  16461.769    9.0  P16
## 74  74 52.2069 -12.2312 697.5  87346.327   61.5  P16
## 75  75 52.3952 -12.4823 601.5 180749.625  128.9  P16
## 76  76 52.4483 -12.7148 603.5  49445.277   33.0  P16
## 77  77 52.5373 -12.9262 550.0 114080.960   88.5  P16
## 78  78 52.3982 -13.1029 543.5  66356.822   43.5  P16
## 79  79 52.1400 -13.2446 606.5  34422.789   24.0  P16
## 80  80 52.0511 -13.5145 495.5  40089.955   24.0  P16
## 81  81 51.8873 -13.5214 581.0  42218.891   30.0  P16
## 82  82 51.7320 -13.4943 710.5  17970.015   12.0  P16
## 83  83 51.4595 -13.6170 723.5  23478.261   13.5  P16
## 84  84 51.2955 -13.7462 686.0  13403.298    7.5  P16
## 85  85 51.2869 -14.0051 522.5  51094.453   33.0  P16
p<-ggplot2::ggplot(hake)+
  geom_polygon(aes(long,lat,group=group),data=Porc,fill="white",color="darkgrey")+
  geom_point(aes(x=long,y=lat,size=sqrt(numero),text=lan),color="blue")+
  scale_size_continuous(name="No. ind.")+coord_fixed(1.3)
## Warning: Ignoring unknown aesthetics: text
ggplotly(p,tooltip=c("text","lance"),width=800,height=500)
library(knitr)
library(kableExtra)
## 
## Attaching package: 'kableExtra'
## The following object is masked from 'package:dplyr':
## 
##     group_rows
options(knitr.table.format = "markdown") 
kable(databICES(1,50,"N16","Cant"),digits=2,caption="Merluza en 2016 Cantábrico y Galicia") %>%
  kable_styling(bootstrap_options="condensed",full_width=F,position="center")
## Warning in kable_styling(., bootstrap_options = "condensed", full_width = F, :
## Please specify format in kable. kableExtra can customize either HTML or LaTeX
## outputs. See https://haozhu233.github.io/kableExtra/ for details.
Merluza en 2016 Cantábrico y Galicia
9.aN_Avg 9.aN_SE 8.cW_Avg 8.cW_SE 8.cE_Avg 8.cE_SE Tot_Avg Tot_SE
Merluccius merluccius_N16_p 12.84 2.35 9.52 1.40 4.77 0.47 7.68 0.65
Merluccius merluccius_N16_n 302.93 44.60 327.89 46.93 107.67 14.37 211.56 18.35
Nort<-ggplot2::map_data(Nort.map)
head(Nort)
ggplot2::ggplot(data=Nort)+geom_polygon(aes(long,lat,fill=region,group=group),col="white")+
  coord_fixed(1.3)